An experimental investigation on friction characteristics of air flow in microtube with structured surface roughness

This paper was presented at the 3rd Micro and Nano Flows Conference (MNF2011), which was held at the Makedonia Palace Hotel, Thessaloniki in Greece. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, Aristotle University of Thessaloniki, University of Thessaly, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute.Experiments were conducted in this research to investigate roughness effect to flow characteristics and heat transfer coefficient of air and CO2 flow in circular micro-tubes. The internal surface of tested tube included smooth, structure helical fin surfaces and random roughness surfaces. Smooth tube is a commercial S. S. 304 tube with internal diameter of 962 μm and average roughness Ra=0.8 μm, while rough circular tubes were lab made Nickel tube with diameters ranging from 926 μm to 977 μm and roughness elements from 5.3 μm to 44.6 μm in height. The experimental results indicated that f and Nu in smooth tube was predicted very well by conventional correlations both for air and CO2. In rough tubes the friction factor was significant higher than the prediction of conventional correlations both in laminar and turbulent flow. Heat transfer enhancement in laminar flow is slightly, nevertheless, in turbulent flow the heat transfer enhancement was significant and the enhancement increases with the increasing of Re. The random rough tubes revealed a higher heat transfer enhancement than the structured helical fin tubes

Towards Multi-class Object Detection in Unconstrained Remote Sensing Imagery

Automatic multi-class object detection in remote sensing images in unconstrained scenarios is of high interest for several applications including traffic monitoring and disaster management. The huge variation in object scale, orientation, category, and complex backgrounds, as well as the different camera sensors pose great challenges for current algorithms. In this work, we propose a new method consisting of a novel joint image cascade and feature pyramid network with multi-size convolution kernels to extract multi-scale strong and weak semantic features. These features are fed into rotation-based region proposal and region of interest networks to produce object detections. Finally, rotational non-maximum suppression is applied to remove redundant detections. During training, we minimize joint horizontal and oriented bounding box loss functions, as well as a novel loss that enforces oriented boxes to be rectangular. Our method achieves 68.16% mAP on horizontal and 72.45% mAP on oriented bounding box detection tasks on the challenging DOTA dataset, outperforming all published methods by a large margin (+6% and +12% absolute improvement, respectively). Furthermore, it generalizes to two other datasets, NWPU VHR-10 and UCAS-AOD, and achieves competitive results with the baselines even when trained on DOTA. Our method can be deployed in multi-class object detection applications, regardless of the image and object scales and orientations, making it a great choice for unconstrained aerial and satellite imagery.Comment: ACCV 201

Cancer pain managment: experience of 702 consecutive cases in a teaching hospital in Hong Kong

Effective pain control is essential in the management of patients with cancer. We present here our experience in the management of 702 patients with cancer pain by the Pain Management Team, Department of Anaesthesiology, Queen Mary Hospital. Patients were discharged from the Pain Management Team with a visual analogue scale of pain (VAS) less than 3 in 87.7% of cases, and more than 90% of patients had improved appetite and sleep on discharge. These promising results were achieved through an emphasis on comfort and function, close liaison among clinicians from different specialties, and a variety of analgesic modalities. Oral drugs remained the mainstay of treatment, supplemented by alternative routes of drug administration such as subcutaneous, intravenous and transdermal delivery. Main side effects observed included nausea (16%) and constipation (8%). Neural blockade, including coeliac plexus blockade, and intercostal nerve blockade, and administration of opioids via subarachnoid or epidural routes were also employed in selected patients.published_or_final_versio

Stable isotopic and biomarker evidence of terrigenous organic matter export to the deep sea during tropical storms

The global export of organic carbon (OC) is intimately linked to the total flux of terrestrial sediment to the ocean, with the continental margins receiving similar to 90% of the sediment generated by erosion on land. Recent studies suggest that a substantial amount of particulate OC (POC) might escape from the shelf and be exported to the continental slope-deep sea sector, although the mechanisms and magnitude of such deep sea POC transfer remain unknown. Here we investigate hyperpycnal flow-associated total suspended matter (TSM) collected from water depths of similar to 3000 m, near the bottom of sea floor, in the Gaoping Submarine Canyon (GSC) off southwestern Taiwan. Elemental (C, N), isotopic (delta C-13, delta N-15) and biomarker compositions of TSM were investigated to understand its biogeochemical characteristics. A two end-member delta C-13 mixing model indicates that deep sea TSM contains similar to 90% terrigenous OC, while a similar mixing model using delta N-15 reveals a lower proportion (similar to 58%). Organic biomarkers of TSM suggest contributions from a mixture of resuspended, continental-margin derived marine organic matter (OMMAR) and terrigenous sources, revealing that terrestrial OC likely mixes with nitrogen-rich marine material during rapid transport. This study documents that rapid transfer of terrigenous organic matter (OMTERR) into the deeper regions of GSC occurred within a week of typhoon Morakot, likely through hyperpycnal injection of sediment-laden, warm freshwater from southern Taiwan. Evidence from this typhoon Morakot-induced hyperpycnal plume event in Taiwan demonstrates that extreme storm events provide an efficient way to export terrigenous OC without oxidation to hitherto unknown water depths of deep sea in the Oceania region. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND licens

Out-of-pocket expenditure associated with physical inactivity, excessive weight and obesity in China: quantile regression approach

Introduction: Previous studies exploring associations of physical inactivity, obesity and out-of-pocket expenditure (OOPE) mainly used traditional linear regression, little is known about the effect of both physical inactivity and obesity on OOPE across the percentile distribution. This study aims to assess the effects of physical inactivity and obesity on OOPE in China using a quantile regression approach. Methods: Study participants included 10,687 respondents aged 45 years and older from the recent wave of the China Health and Retirement Longitudinal Study in 2015. Linear regression and quantile regression models were used to examine the association of physical activity, body weight with annual OOPE. Results: Overall, the proportion of overweight and obesity was 33.2% and 5.8%, respectively. The proportion of individuals performing high-level, moderate-level and low-level physical activity was 55.2%, 12.7% and 32.1%, respectively. The effects of low-level physical activity on annual OOPE was small at the bottom quantiles but more pronounced at higher quantiles. Respondents with low-level activity had an increased annual OOPE of 26.9 US$, 150.3 US$, 1534.4 US$, at the 10th, 50th, and 90th percentiles, respectively, compared with those with high-level activity. The effects of overweight and obesity on OOPE were also small at the bottom quantiles but more pronounced at higher quantiles. Conclusion: Interventions that improve the lifestyles and unhealthy behaviours among people with obesity and physical inactivity are likely to yield substantial financial gains for the individual and health systems in China

Proteome profiling of cadmium-induced apoptosis by antibody array analyses in human bronchial epithelial cells

Protein array technology is a powerful platform for the simultaneous determination of the expression levels of a number of proteins as well as post-translational modifications such as phosphorylation. Here, we screen and report for the first time, the dominant signaling cascades and apoptotic mediators during the course of cadmium (Cd)-induced cytotoxicity in human bronchial epithelial cells (BEAS-2B) by antibody array analyses. Proteins from control and Cd-treated cells were captured on Proteome Profiler™ Arrays for the parallel determination of the relative levels of protein phosphorylation and proteins associated with apoptosis. Our results indicated that the p38 MAPK- and JNK-related signal transduction pathways were dramatically activated by Cd treatment. Cd potently stimulates the phosphorylations of p38α (MAPK14), JNK1/2 (MAPK8/9), and JUN; while the phosphorylations of Akt1, ERK1/2 (MAPK3/1), GSK3β, and mTOR were suppressed. Moreover, there was an induction of proapoptotic protein BAX, release of cytochrome c (CYCS) from mitochondria, activation of caspase-3/9 (CASP3/9); as well as decreased expression of cell cycle checkpoint proteins (TP53, p21, and p27) and several inhibitors of apoptosis proteins (IAPs) [including cIAP-1/2 (BIRC2/3), XIAP (BIRC4), and survivin (BIRC5)]. Pretreatment of cells with the thiol antioxidant glutathione or p38 MAPK/JNK inhibitors before Cd treatment effectively abrogated ROS activation of p38 MAPK/JNK pathways and apoptosis-related proteins. Taken together, our results demonstrate that Cd causes oxidative stress-induced apoptosis; and the p38 MAPK/JNK and mitochondrial pathways are more importantly participated for signal transduction and the induction of apoptosis in Cd-exposed human lung cells.published_or_final_versio

Ellagic acid, a phenolic compound, exerts anti-angiogenesis effects via VEGFR-2 signaling pathway in breast cancer

Anti-angiogenesis targeting VEGFR-2 has been considered as an important strategy for cancer therapy. Ellagic acid is a naturally existing polyphenol widely found in fruits and vegetables. It was reported that ellagic acid interfered with some angiogenesis-dependent pathologies. Yet the mechanisms involved were not fully understood. Thus, we analyzed its anti-angiogenesis effects and mechanisms on human breast cancer utilizing in-vitro and in-vivo methodologies. The in-silico analysis was also carried out to further analyze the structure-based interaction between ellagic acid and VEGFR-2. We found that ellagic acid significantly inhibited a series of VEGF-induced angiogenesis processes including proliferation, migration, and tube formation of endothelial cells. Besides, it directly inhibited VEGFR-2 tyrosine kinase activity and its downstream signaling pathways including MAPK and PI3K/Akt in endothelial cells. Ellagic acid also obviously inhibited neo-vessel formation in chick chorioallantoic membrane and sprouts formation of chicken aorta. Breast cancer xenografts study also revealed that ellagic acid significantly inhibited MDA-MB-231 cancer growth and P-VEGFR2 expression. Molecular docking simulation indicated that ellagic acid could form hydrogen bonds and aromatic interactions within the ATP-binding region of the VEGFR-2 kinase unit. Taken together, ellagic acid could exert anti-angiogenesis effects via VEGFR-2 signaling pathway in breast cancer. © 2012 The Author(s).published_or_final_versio

Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images

Human pose estimation (HPE) is a key building block for developing AI-based context-aware systems inside the operating room (OR). The 24/7 use of images coming from cameras mounted on the OR ceiling can however raise concerns for privacy, even in the case of depth images captured by RGB-D sensors. Being able to solely use low-resolution privacy-preserving images would address these concerns and help scale up the computer-assisted approaches that rely on such data to a larger number of ORs. In this paper, we introduce the problem of HPE on low-resolution depth images and propose an end-to-end solution that integrates a multi-scale super-resolution network with a 2D human pose estimation network. By exploiting intermediate feature-maps generated at different super-resolution, our approach achieves body pose results on low-resolution images (of size 64x48) that are on par with those of an approach trained and tested on full resolution images (of size 640x480).Comment: Published at MICCAI-201

A procedure for the change point problem in parametric models based on phi-divergence test-statistics

This paper studies the change point problem for a general parametric, univariate or multivariate family of distributions. An information theoretic procedure is developed which is based on general divergence measures for testing the hypothesis of the existence of a change. For comparing the accuracy of the new test-statistic a simulation study is performed for the special case of a univariate discrete model. Finally, the procedure proposed in this paper is illustrated through a classical change-point example

Modelling of content-aware indicators for effective determination of shot boundaries in compressed MPEG videos

In this paper, a content-aware approach is proposed to design multiple test conditions for shot cut detection, which are organized into a multiple phase decision tree for abrupt cut detection and a finite state machine for dissolve detection. In comparison with existing approaches, our algorithm is characterized with two categories of content difference indicators and testing. While the first category indicates the content changes that are directly used for shot cut detection, the second category indicates the contexts under which the content change occurs. As a result, indications of frame differences are tested with context awareness to make the detection of shot cuts adaptive to both content and context changes. Evaluations announced by TRECVID 2007 indicate that our proposed algorithm achieved comparable performance to those using machine learning approaches, yet using a simpler feature set and straightforward design strategies. This has validated the effectiveness of modelling of content-aware indicators for decision making, which also provides a good alternative to conventional approaches in this topic